Outputs

ESR project outputs

ESR 1 - Rafael Sanchez Martinez

Castration resistant prostate cancer (CRPC) is a currently incurable form of prostate cancer that develops after prostate cancer is treated with androgen deprivation therapy (ADT), a widely used form of treatment. A previous study in our group had pointed at the SLFN5 protein as a potentially important player in CRPC. Our studies showed that the expression of this protein is controlled by androgens and that it can affect tumour growth under androgen deprived conditions. We confirmed the increased presence of SLFN5 in CPRC clinical samples in collaboration with the Vancouver Prostate Centre. Our biological experiments showed that SLFN5 expression affects amino acid balance, metabolism related growth signalling (mTOR), and that it controls the expression of LAT1 amino acid transporter, potentially allowing the cancer cells to obtain more nutrients and grow faster. These results suggest SLFN5 might have a role in the transformation prostate cancer cells undergo after ADT to survive and thrive after the treatment, and therefore would constitute a putative clinical target.

ESR 2 - Parmveer Singh

Prostate cancer is one of the leading causes of death among men in developed countries. Advances in uncovering the mechanisms of this disease have been hindered due to the absence of a sufficient human model that incorporates the complexity and variability of the disease. Current models have inherent disadvantageous, which prevents a complete understanding of the disease. Recently, patient-derived prostate organoids have emerged as an additional tool to complement current models. Our group developed a protocol to produce prostate organoids using induced pluripotent stem cells (iPSCs). Generating organoids using iPSCs is beneficial over the use of primary tissue because they are more accessible by all researchers and have a longer life span in culture compared. This research focused on the optimization of iPSC differentiation and prostate organoid generation using seminal vesicle mesenchyme (SVM) and urogenital sinus mesenchyme (UGM) as a source of inductive factors. iPSCs were first differentiated into definitive endoderm and then co-cultured with rat SVM/UGM. The optimal culture conditions to produce prostate organoids were established, with the organoids expressing the androgen receptor, PSA, Nkx3.1, and basal and luminal markers. Some organoids also displayed a branching morphogenesis phenotype though, not all organoids showed the full array of these markers, indicating some optimization is still required. This model is now being used to produce organoids from genetically modified stem cells using an inducible CRISPR-Cas9 systems to recapitulate prostate carcinoma phenotypes in mature organoids. Additionally, we sought to elucidate the genetic pathways involved in prostate induction through RNA-sequencing of the UGM/SVM and associated epithelium. Preliminary results have shown that the tissues are enriched for genes with functions involved in prostate development. The sequencing analysis has provided a list of candidate genes that may be key for prostate induction. Inductive factors revealed from expression profiling could be evaluated for their ability to differentiate iPSCs to prostate tissue. Being able to produce organoids from iPSCs without rodent tissue would further improve this model to study prostate cancer.

ESR 4 - Syeda Afshan

Prostate cancer (PCa) is the most diagnosed cancer in men of developed countries. Fibroblast growth factor receptors (FGFRs) play an important role in PCa initiation and progression. Fibroblast growth factor receptor like 1 (FGFRL1) is the most recently identified member of the FGFR family. Its extracellular domain shares high similarity to FGFR1-4, but the intracellular tail lacks the canonical tyrosine kinase domain required for FGF-induced signaling. My doctorate thesis investigates the role of FGFRL1 and its molecular function in the progression of PCa. We observed up-regulation of FGFRL1 mRNA expression in genome-wide cancer transcriptome studies. Moreover, mRNA and protein expression of FGFRL1 was found to be upregulated in a PCa patient sample cohort (n=150) from the university clinics of Turku and Helsinki, Finland. We decided to explore the functions of FGFRL1 in PCa progression.

Androgen receptor (AR) is a transcription factor, which plays a key role in the development and progression of prostate cancer (PCa) and is the main therapeutic target for treatment of PCa. In a fraction of patients, PCa acquires resistance to androgen deprivation therapy, and progresses to castration-resistant PCa (CRPC), for which there is no cure. In a small subset of patients, tumours progress towards neuroendocrine (NE) differentiation, while others bypass both AR and NE dependence and progress through fibroblast growth factor (FGF) signalling.
We use established PCa cell lines like PC3M, LNCaP and VCaP also study the influence of FGFRL1 expression and functions on the AR pathway and signalling in PCa. These are applied in vitro 2D functional studies, 3D organotypic monoculture and coculture models, in vivo xenograft models in order to investigate and validate our hypotheses. At a later time point, we aim to use our collection of patient-derived PCa samples to further validate our findings for the potential use in anti-cancer therapy.

ESR 5 - Annelies van Hemelryk

Castration-resistant prostate cancer (CRPC) encompasses a highly heterogeneous disease spectrum that is currently still incurable. Appropriate preclinical models that exemplify the contemporary CRPC landscape are crucial to expand insights into this lethal stage of prostate cancer (PCa). During my research, I addressed two major concerns in PCa modelling: (i) the scarcity of representative CRPC models, specifically from heavily pretreated patients; (ii) the need for an in vitro model that allows for expansive research, but at the same time adequately mirrors patient tumors. We developed five CRPC patient-derived xenografts (PDXs) that display an adenocarcinoma phenotype and maintain an active AR signalling pathway, in correspondence with the original patient tumor. Assessing in vivo taxane responses of PDXs demonstrated a high resemblance to the retrospectively retrieved clinical responses of matched patients. Further genomic analysis will now focus on the identification of new potential targets for intervention. In parallel, I constructed a workflow to create organoids both from these xenografts and from primary patient tissues. Importantly, organoids preserved the morphological, immunohistochemical, transcriptomic and genomic features of the tumors they were derived from, making them a valid in vitro substitute. To apply these organoids for preclinical drug testing, I designed a dedicated protocol that enables large-scale proliferation assays on established PCa organoids. Subsequently retrieved organoid responses to docetaxel and cabazitaxel clearly mimicked the taxane responses of corresponding PDXs. Currently, we are optimizing an alternative high-content organoid drug screening approach by using live cell imaging, that will allow for more specific read-outs (e.g. cytostasis, apoptosis, necrosis). Overall, this diversified and clinically-relevant panel of patient-derived CRPC models, including both PDXs and organoids, can serve as a valuable tool to identify and validate molecular targets of progressive disease; while our dedicated PCa organoid drug testing platforms can contribute to novel therapeutic strategies for CRPC and facilitate drug discovery or drug repurposing.

ESR 6 - Marouane Kdadra

Prostate cancer remains a significant medical challenge. The current diagnosis and prognosis tools often result in unnecessary invasive procedures as well as over-diagnosis and over-treatment highlighting the need for novel biomarkers. Despite recent progress in therapy, resistance to androgen deprivation therapy in advanced prostate cancer is inevitable causing the devolvement of a lethal form of disease called castration resistant prostate cancer.

The aim of our project was to identify biomarkers for monitoring progression of prostate cancer and castration resistant prostate cancer. We first identified a panel of 12 biomarkers that were able to distinguish between patients who responded to treatment and those who developed castration resistant prostate cancer. Then we tested the ability of these biomarkers to detect prostate cancer and assess its aggressiveness. Finally, we integrated our metabolites with transcriptomics and proteomics data in an attempt to discover altered pathways in prostate cancer progression. Tyrosine metabolism pathway was particularly associated with aggressive prostate cancer.

Our findings will complement the knowledge of the biology behind the specific steps of the castration resistance prostate cancer and ultimately, help to ameliorate the clinical management of patients with CRPC by finding novel therapeutic targets.

ESR 8 - Mina Sattari

Prostate cancer (PC) is one of the most important causes of cancer-related death in men. There is a critical need to identify biomarkers that can distinguish indolent PC from the aggressive form of this disease. It has been previously shown that Long non-coding RNAs (lncRNAs) play a considerable role in tumorigenesis by being involved in critical processes in cancer. In the current study, the aim was to identify lncRNAs with strong differential expression between primary tumors and metastases as novel putative biomarkers and therapeutic targets.

We performed a comprehensive gene expression analysis using next-generation sequencing platforms to explore lncRNAs from PC tissue samples, including local castration-resistant prostate cancer (CRPCs), and metastatic CRPCs.

A total of 42 lncRNAs were identified as significantly differentially expressed in metastases as compared to primary tumors. Of the 42 lncRNAs, 36 lncRNAs were upregulated, and 6 lncRNAs were downregulated in metastatic PCs.

Transcription factor enrichment analysis revealed that the majority of the lncRNAs of interest are driven by the most important PC-specific transcription factors, such as AR, HOXB13, FOXA1, EZH2, BRD4, and SMAD2. Furthermore, among the significant lncRNAs that had binding sites for AR, we found two upregulated lncRNAs showing higher expression levels in LNCaP and VCaP cells in response to DHT stimulation and lower expression levels in cells with siRNA-mediated AR-knockdown.

In summary, our findings indicate AR-regulated lncRNAs that may play a role in the progression of PC. Further experiments will be performed to evaluate the potential value of the candidate lncRNAs as PC biomarkers.

ESR9 - Mario Cangiano

 The efficient clinical management of prostate cancer (PCa) is hampered by the low specificity of PSA screening, the diffused inter- and intra-tumors heterogeneity and the lack of an accurate criteria to discriminate patients who would benefit from active surveillance from the ones who need definitive treatment. Overtreatment leads to the progressive growth towards more aggressive and untreatable castration resistant (CRPC) and neuroendocrine (NEPC) PCa variants. It is, therefore, of the utmost importance to develop new tools that would aid patient stratification.

It has been shown that the transcriptional reprogramming is a hallmark of PCa and that single genes are not likely to show prognostic insights in such a complex disease. Taking that into account, we decided to focus our attention on a pipeline aimed to profile transcription factors activity on a single sample level, by leveraging the correlations of the expression profiles among multiple genes. A gene regulatory network (GRN) has been inferred from nude immune mice orthografts. Such network constitutes of regulons, sets of genes under the (positive or negative) regulation of the same transcription factor. The GRN was then enriched with differentially expressed genes calculated from three independent retrospective radical prostatectomies cohorts, to identify sample specific active transcription factors. Cox regression revealed the prognostic potential of JMJD6 regulon enrichment when using biochemical recurrence as clinical endpoint. JMJD6, therefore, could aid patients risk stratification and, more importantly, since JMJD6 is a targetable molecule, it could offer an alternative therapeutic strategy.

ESR 10 - Cathal McKinney

Two novel transcriptomic subtypes of primary prostate cancer (PCa) were discovered using the Almac tool claraT and a novel adaptation of the compositional data analysis tool, Gene Expression Compositional Assignment (GECA). Six hallmarks of cancer were assessed by claraT including Immuno-Oncology, epithelial-to-mesenchymal transition (EMT), Angiogenesis, Genome-Instability (GI) Proliferation and Cell Death. Of the six hallmarks represented amongst 51 gene expression signatures, GI was determined to be most prognostically relevant. Consensus clustering using the nine GI signature scores identified two stable clusters with distinct prognoses. Two prognostic clusters were discovered in each of the four datasets investigated: Walker et al. II (MFS log-rank, p=7.7451e-09), Jain et al (MFS log-rank, p=0.0102), TCGA (DFS log-rank, p=0.0043) and Walker et al. II (chi-square – metastases, p=1.5052e-05).

Using the novel GECA subtype discovery methodology, the two clusters of each dataset were grouped together based on degree and significance of their similarity. Two transcriptionally similar groups of clusters or subtypes were identified and determined to be stable by assessing the edge significance of the cluster-cluster pairs within each subtype (p<0.05). The poor prognosis Genome-Unstable subtype was characterised by high expression of the GI signatures and high CNA levels relative to the Genome-Stable subgroup (Wilcoxon, p=9.2911e-15).

Differential gene expression analysis and subsequent KEGG pathway analysis, identified four pathways as significantly enriched: Cell cycle, Ooxyte meiosis, DNA replication and p53 signalling (<0.05 with Bonferroni correction). DNA polymerase theta (POLQ) was identified as a predictive biomarker of the poor prognostic GI subtypes (Wilcoxon, p=0.0009896. POLQ was further validated as a poor prognostic biomarker in the Stand Up To Cancer (SU2C) cohort of castration resistance prostate cancer (CRPC) patients (OS log-rank, p=8.15e-05). The Genome-Unstable subtype with a dominant GI biology may therefore represent a target subgroup of primary PCa, which could benefit from DNA repair-targeted therapies such as POLQ- and/or PARP-inhibitors.

ESR 11 - Ingrid Tomljanovic

According to global cancer statistics (GLOBOCAN) 2018 estimates, prostate cancer is the second most frequent malignancy in men worldwide. It is a highly heterogeneous disease that exhibits a pressing need for developing personalized medicine approaches that could lead to a better diagnosis, prognosis, and treatment of patients. Therefore, it is of crucial importance to generate preclinical models of prostate cancer that adequately represent the original patient tumors and as such can be used in further basic and translational research.

The aim of this project was to demonstrate the molecular characteristics and consistency between samples of a novel panel of preclinical models established in part by TransPot ESR5 at the Erasmus MC in Rotterdam. These included patient-derived xenografts (PDXs) and matching PDX-derived organoids (PDXOs) on which RNA sequencing was performed. Bioinformatics analyses were employed to investigate whether aspects such as gene expression are preserved between the PDXs and the organoids that were derived from them. A demonstrated patient-of-origin based grouping of the samples suggested that the organoids recapitulate multiple aspects of the original PDX tumors and could be amenable for future studies involving various stages of disease progression. Furthermore, efforts are ongoing to identify and select druggable targets in a subset of the organoids to be used for drug testing in vitro.

An additional separate project has been initiated to leverage various datasets generated within the consortium to conduct a systems biology evaluation of potential biomarkers for castration-resistant prostate cancer, which is an aggressive and lethal form of cancer characterized by resistance to therapy. In summary, the impact of this work lies in generating insights that could enhance translational research efforts against prostate cancer.

TransPot Publications

Curry E.L., Moad M, Steele R.E., Franco O.E., Wilson L, Singh P, Buskin A, Crawford S.E., Gaughan L, Mills I.G., Hayward S.W., Robson C.N., Heer R, (2020 Jul): Propagation of human prostate tissue from induced pluripotent stem cells, STEM CELLS Translational Medicine, DOI: 10.1002/sctm.19-0286

Van Hemelryk A, M. van Weerden W, (2020): Novel patient-derived 3D culture models to guide clinical decision-making in prostate cancer, Current Opinion in Endocrine and Metabolic Research, DOI: 10.1016/j.coemr.2020.02.005 

Mantsiou A, Makridakis M, Fasoulakis K, Katafigiotis I, Constantinides C.A., Zoidakis J, Roubelakis M.G., Vlahou A, Lygirou V, (2019 Nov): Proteomics Analysis of Formalin Fixed Paraffin Embedded Tissues in the Investigation of Prostate Cancer, Journal of Proteome Research, DOI: 10.1021/acs.jproteome.9b00587

Kdadra, M., Höckner, S., Leung, H., Kremer, W., Schiffer, E., (2019): Metabolomics Biomarkers of Prostate Cancer: A Systematic Review, Diagnostics, DOI: 10.3390/diagnostics9010021

Hepburn A.C.,Steele R.E.,Veeratterapillay R,Wilson L,Kounatidou E.E., Barnard A, Berry P, Cassidy J.R., Moad M, El-Sherif A, Gaughan L, Mills I.G., Robson C.N., Heer R, (2019 Feb): The induction of core pluripotency master regulators in cancers defines poor clinical outcomes and treatment resistance, Oncogene, DOI: 10.1038/s41388-019-0712-y

Mantsiou, A., Vlahou, A. and Zoidakis, J., (2018): Tissue proteomics studies in the investigation of Prostate cancer, Expert Review of Proteomics,  DOI: 10.1080/14789450.2018.1491796

Abstracts

Abstracts from ESUR 2019 conference, Porto, Portugal, 10th – 12th October 2019 https://esur.uroweb.org/

ESR 1 Rafael Sanchez Martinez - SLFN5 regulates amino acid metabolism by altering LAT1 expression in CRPC

ESR 2 Parmveer Singh - In vitro prostate tissue generation using induced pluripotent stem cells and rodent seminal vesicle mesenchyme

ESR 3 Syed Umbreen - Evaluating multicellular contributions to the maintenance of AR activity under conditions of androgen deprivation

ESR 4 Syeda Afshan - Study on the possible interactions between FGFRL1- and AR-regulated mechanisms in prostate cancer

ESR 5 Annelies Van-Hemelryk - A novel panel of patient-derived preclinical models of prostate cancer: xenografts and PDX-derived organoids to recapitulate patients disease profiles

ESR 6 Kdadra Marouane - Assessment of Prostate Cancer Aggressiveness using metabolomics evaluation of urine by NMR Spectroscopy

ESR 7 Anna Mantsiou - Proteomics analysis of Formalin Fixed Paraffin Embedded tissues in the investigation of prostate cancer

ESR 8 Mina Sattari - Identification of novel long non-coding RNA based biomarkers in prostate cancer

ESR 9 Mario Cangiano - A transcription factor activity profile as a prognostic signature for recurrence predisposition in prostate cancer patients

ESR 10 Cathal McKinney - A meta-analytical approach to the molecular subtyping of prostate cancer

Abstracts from ESUR 2018 conference, Athens, Greece, 4th – 6th October 2018  https://esur.uroweb.org/ 

ESR 1 Rafael Sanchez Martinez - Regulation of SLFN5 by androgens in castration resistant prostate cancer

ESR 2 Parmveer Singh - In vitro prostate differentiation of induced pluripotent stem cells and organoid generation using seminal vesicle mesenchyme

ESR 3 Syed Umbreen - Approaches to enrich for androgen receptor binding sites in low-cell number samples

ESR 5 Annelies Van-Hemelryk - Establishment of prostate cancer organoids: tips, tricks and pitfalls

ESR 7 Anna Mantsiou - Proteomic studies in clinical tissues for the investigation of prostate cancer

ESR 9 Mario Cangiano - Network analysis of prostate cancer-derived CWR22, LNCaP and VCAP xenografts for elucidation of the key regulators in castration resistance development

ESR 10 Cathal McKinney - A meta-analytical approach to the molecular subtyping of prostate cancer

 

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